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Article

The Effect of Different Remediation Treatments on Soil Fungal Communities in Rare Earth Tailings Soil

by
Yu Wang
1,2,†,
Feng Pan
2,3,†,
Qiong Wang
1,2,
Jie Luo
4,
Qin Zhang
5,
Yingying Pan
1,2,
Chenliang Wu
1,2 and
Wei Liu
1,2,*
1
Jiangxi Provincial Key Laboratory of Silviculture, Jiangxi Agricultural University, Nanchang 330045, China
2
School of Art and Landscape, College of Forestry, Jiangxi Agricultural University, Nanchang 330045, China
3
Jiangxi Academy of Water Science and Engineering, Nanchang 330029, China
4
School of Resources Environment and Jewelry, Jiangxi College of Applied Technology, Ganzhou 341000, China
5
Key Laboratory of Poyang Lake Watershed Agricultural Resources and Ecology of Jiangxi Province, College of Land Resource and Environment, Jiangxi Agricultural University, Nanchang 330045, China
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Forests 2022, 13(12), 1987; https://doi.org/10.3390/f13121987
Submission received: 21 October 2022 / Revised: 18 November 2022 / Accepted: 18 November 2022 / Published: 24 November 2022
(This article belongs to the Special Issue Assessments and Restoration Technique of Forest Land Development in Hilly Areas)
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Abstract

:
Extensive mining of rare earth deposits has caused severe soil erosion, resulting in the degradation of plant–soil systems and the reduction in microbial diversity. Combined ecological remediation technology is the key method of vegetation reconstruction and ecological restoration in abandoned tailings. In this study, the effects of different cover crops–biochar–organic fertilizer and biochar–organic fertilizer treatments on soil fungal communities in rare earth tailings soil were analysed using high-throughput sequencing technology. Linear discriminant analysis effect size (LEfSe) was used to analyse saprophytic, mycorrhizal, and potential pathogenic fungi in soils after different combined remediations. Moreover, the effects of soil environmental factors on fungal community species’ composition were analysed by redundancy analysis (RDA) and variance partitioning analysis (VPA) after different combined remediations. LEfSe indicated a risk of citrus pathogenicity by Diaporthaceae indicator fungi after biochar–organic fertilizer combined treatment. RDA and VPA revealed that pH was the main environmental factor affecting the fungal community in the different combined remediation treatments. Additionally, the Paspalum wettsteinii cover crops–biochar–organic fertilizer and biochar–livestock manure treatments were more conducive to arbuscular mycorrhizal fungi recruitment. We also clarified the fungal community composition structure, soil environmental factors, and fungal community relationships in rare earth tailings soil after different combined remediation treatments.

1. Introduction

Rare earth elements (REEs) is the general term for yttrium (Y), scandium (Sc), and 15 types of lanthanide metal elements, known as ‘modern industrial vitamins’ [1]. China has the richest reserves of rare earth resources, accounting for 50% of the world’s reserves [2]. Ionic rare earth deposits are one of the major rare earth deposits in the world, are mainly found in southern China [3], and have been widely exploited in Jiangxi Province in recent decades. Ionic rare earth is mainly adsorbed onto clay minerals in the form of hydrated cations or hydroxyl hydrated cations, and electrolyte ion (Na+, NH4+, H+, and Mg2+) exchange chemical methods are used for ion-type REE beneficiation [4]. Ammonium sulfate solution heap leaching extraction of REEs causes serious damage to surface vegetation [5], resulting in a large number of leaching agent residues, soil erosion, soil acidification, serious soil degradation, fertility decline, rare earth heavy metal pollution, and decreased soil microbial community abundance and diversity [6,7,8,9]. Moreover, it also threatens the surrounding environment and residents [10]. Mining degenerates the plant–soil system, so the need to restore the ecological system structure, composition, and function is particularly urgent [11].
Rare earth mining soil remediation methods mainly include physical, chemical, and biological remediation methods. However, the traditional physical strategy frequently employs high-intensity artificial processes, such as soil material input and terrain treatment [12]. Chemical and biological remediation strategies mainly focus on organic amendment addition and pioneer plant cultivation [13]. Among the physical, chemical, and biological remediation methods, researchers have paid increasing attention to bioremediation in recent years as society shifts to sustainable and green solutions to environmental problems. Bioremediation avoids the risk of secondary soil contamination associated with chemical remediation and effectively promotes soil fertility [4]. Bioremediation also improves soil structure and fertility through the life activities and metabolism of living organisms. In recent decades, scholars have combined multidisciplinary research for mine remediation to restore mine landscapes [14]. However, mine remediation remains essentially a process of ecosystem restoration and rehabilitation. The restoration and reconstruction of natural ecosystems are often closely related to vegetation. Before the establishment of vegetation, the chemical properties of the soil of rare earth mines need to be adjusted by adding soil amendments. It was reported that the application of bamboo biochar and coal fly ash as soil additives significantly increased the pH, cation exchange capacity (CEC), and organic matter content of the soil; when bamboo biochar and coal fly ash were combined to grow cabbage, it was found that cabbage could not be grown with bamboo biochar alone [15]. The combined application of sawdust and biochar significantly enhanced rare earth ore improvement compared with their single application [16]. Clearly, a single remediation method or soil amendment is unable to achieve the goal of rare earth mine remediation. The combined ecological remediation technology of co-application of multiple soil modifiers or of soil modifier–vegetation is more effective in restoration. According to the formation causes and terrain types of abandoned tailings, combined ecological remediation technology is the key method of vegetation reconstruction and ecological restoration in abandoned tailings [17]. Combined remediation technology can play to the respective advantages of each soil additive, eliminate shortcomings, and optimize the repair effect.
Soil microbes are important components of the Earth’s biodiversity and soil ecosystems [18] and play a crucial role in maintaining soil productivity, health, and sustainability [19]. Fungi are one of the richest and most important microorganisms in the soil and are involved in important ecological functions in soil ecosystems, such as nutrient transformation and organic matter decomposition [20,21]. During recent decades, the combined remediation of rare earth mines has focused more on bacteria in the study of microbial communities, ignoring the role of fungal communities [22,23]. Fungi are extremely important in driving plant diversity and productivity. Plant–fungus associations can greatly contribute to plant growth, persistence, community diversity, and productivity in ecosystems [20]. A recent study showed that fungi are more adaptable to harsh soil environments than bacteria [24], and fungi may play a more important role in the ecological restoration and reclamation of rare earth mines.
At present, most studies have focused on combined remediation of soil quality, rare earth elements content, and bacterial communities of rare earth tailings. Little attention has been paid to soil fungal communities on different combined remediations of rare earth tailings. How does combined remediation (soil amendments, cover crops, beneficial fungi) contribute to the restoration of rare earth tailings-affected plant–soil ecosystems, and how can soil fungal resources be used to promote soil health for reclaimed soil productivity enhancement? In this study, we used high-throughput sequencing technology to compare the fungal communities of soils with the long-term application of different organic fertilizers (organic fertilizer, cattle manure, pig manure) and with low levels of added biochar. At the same time, cover crops (Trifolium repens L., Paspalum wettsteinii) were compared to surface planting, and low-level bamboo biochar and organic fertilizer were applied. The main objective of this study was to investigate the effects of different combined remediations on soil fungal communities, and we hypothesized that different combined remediation methods would select for different soil fungal communities. Specifically, our hypotheses were that (1) different combined remediations are conducive to the reclamation of rare earth tailings–navel orange planting soil; (2) different combined remediations change the composition and structure of fungal communities; and (3) different combined remediations drive different major environmental factors affecting fungal communities.

2. Materials and Methods

2.1. Site and Experimental Design

The experimental site was located in Dingnan County (24°59.2′ N, 115°2.0′ E), Jiangxi Province (Figure 1a). The precipitation and annual average temperatures are 1800 mm and 19 °C, respectively. Red earth is the main soil type. The test material was two-year-old Newhall navel orange trees (Citrus sinensis Osbeck cv. Newhall). The basic soil properties were as follows: pH 4.5, organic matter 1.5 g·kg−1, soil ammonium nitrogen (NH4+-N) 10.1 mg·kg−1, available phosphorus 2.1 mg·kg−1, and available potassium 52.7 mg·kg−1.
There were five treatments in total, including two treatment groups: (1) different cover crops–biochar–organic fertilizer treatments: biochar–organic fertilizer (BD), Trifolium repens L. cover crops–biochar–organic fertilizer (TBD), and Paspalum wettsteinii cover crops–biochar–organic fertilizer (PBD); and (2) different biochar–organic fertilizer treatments: biochar–organic fertilizer (BD), biochar–pig manure (BG), and biochar–cattle manure (BF). The settings for each treatment are summarized in Table A1 (Appendix A). In addition, 1.75 kg calcium magnesium phosphate fertilizer and 0.7 kg coal fly ash were applied to provide basic nutrients and to improve the pH of the tailings soil. Both pig and cattle manure organic fertilizers were produced locally. More details of the soil amendments are provided in Table A2 (Appendix A).
Figure 1 summarizes the experimental set-up. The size of the planting holes was approximately 60 cm × 60 cm × 50 cm (length × width × height). All the amendments were mixed with the rare earth tailings soil, and then 5 cm of tailings soil was applied as mulch after planting the navel orange trees (Figure 1b). The cover crops Trifolium repens L. and Paspalum wettsteinii were sown at a density of 6 g·m−2 within the amendment area. Three plots were set up for each treatment, and the map of each treatment plot is shown in Figure 1c, with green circles indicating navel orange trees.
Two and a half years after planting, soil samples were collected in November 2020. The samples were collected at 30 cm from the citrus tree planting point (Figure 1d), and the topsoil was removed before sampling. Soil samples from the same treatment plots were evenly mixed, and one bag of shallow soil samples (0–20 cm) was collected from each treatment plot (n = 15). All soil samples were divided into two parts. One part was transported to the laboratory in dry ice for DNA extraction and microbial determination. The remaining part was air-dried for the determination of soil parameters.

2.2. Determination of Soil Parameters

Soil pH was measured at a soil–water ratio of 1:2.5 (w/v) using a pH meter. The total nitrogen (TN) was determined by the Kjeldahl method. Soil organic carbon (SOC) was determined by the K2Cr2O7 oxidation method; soil total phosphorus (TP) was determined by H2SO4-HClO4 digestion followed by the molybdenum blue method using the digestion solution [25]. Soil total potassium (TK) was determined using a NaOH melting-flame photometer; soil available phosphorus (AP) was measured after extraction with 0.03 mol·L−1 NH4F [26].

2.3. High-Throughput Sequencing

A TIANamp Soil Microbial Genomic DNA Kit was used to extract soil microbial DNA. The fungal ITS hypervariable regions were amplified with the primers ITS1F (5′-CTTGGTCATTTAGAGGAAGTAA-3′) and ITS2R (5′-GCTGCGTTCTTCATCGATGC-3′) by PCR. All PCRs were carried out with 15 µL of Phusion® High-Fidelity PCR Master Mix (Biolabs, New England, USA). Trimmomatic and FLASH were used for quality control and merging of original sequences. UPARSE software was used to cluster the sequences with 97% similarity into operational taxonomic units (OTUs), and UCHIME was used to eliminate the chimeras. Finally, the Unite Database was used based on the BLAST algorithm to annotate taxonomic information. Sequencing was performed by Novogene Co., Ltd. (Beijing, China) based on an Illumina MiSeq platform (San Diego, CA, USA).

2.4. Statistical Analysis

One-way analysis of variance (ANOVA) with Duncan’s test was performed using SPSS software (version 19.0, Chicago, IL, USA) to analyse the differences in soil environmental variables and fungal diversity with a significance level of p < 0.05. Redundancy analysis (RDA) was performed in Canoco5. The Shannon, Simpson, Chao1, ACE, and coverage indices in our soil samples were calculated with QIIME (version 1.7.0). Fungal community composition analysis, principal coordinates analysis (PCoA), and linear discriminant analysis effect size (LEfSe) were performed using the online platform Novogene Cloud (https://magic.novogene.com/ accessed on 28 September 2022).

3. Results

3.1. Soil Environmental Traits

Table 1 shows that the effects of different cover crops–biochar–organic fertilizer combined remediation treatments on soil physicochemical properties were not significant. The soil pH value in the Paspalum wettsteinii–biochar–organic fertilizer (PBD) treatment was lower than that in the Trifolium repens L.–biochar–organic fertilizer (TBD) and biochar–organic fertilizer (BD) treatments, but the difference was not significant (p > 0.05). The TN, TP, and AP contents of the different biochar–organic fertilizer combined remediation treatments showed a small and nonsignificant change, and the TK contents significantly increased (p < 0.05). The SOC content of the biochar–organic fertilizer (BD) treatment was significantly higher than that of the biochar–cattle manure (BF) and biochar–pig manure (BG) treatments (p < 0.05). The soil pH was significantly lower in the biochar–cattle manure (BF) treatment than in the biochar–pig manure (BG) and biochar–organic fertilizer (BD) treatments (p < 0.05).

3.2. Diversity, Composition, and Structure of the Fungal Community

In this study, the diversity (Shannon and Simpson indices) and abundance (Chao1 estimator) of fungal communities after different combined remediations were also compared (Table 2). The diversity of fungal communities was higher than that of the control (BD) (p < 0.05) in cover crops–biochar–organic fertilizer combined remediation. In the different biochar–organic fertilizer treatments, the diversity of the soil fungal communities increased after applying organic fertilizer (BD), and it decreased after applying livestock manure (BG and BF). There were no significant differences in the diversity or abundance of the different biochar–organic fertilizer combined remediation treatments (p > 0.05). The community coverage index was greater than 0.9950, indicating that the sequencing results were sufficient to represent the actual status of each treatment soil sample (Table 2).
The relative abundance of the fungal community differed significantly at the phylum level among the different combined remediation treatments, with large differences observed (Figure 2). The top 10 phyla in the fungal communities were observed, and some phyla showed different distributions in the different combined remediation treatments. The dominant fungal groups and their relative abundances were Ascomycota (67.73%–82.23%), Basidiomycota (2.86%–15.64%), Mortierellomycota (0.34%–0.77%), Chytridiomycota (0.15%–1.23%), and Glomeromycota (0.20%–1.42%).
Two-dimensional PCoA plots using Bray–Curtis distances were generated to further describe changes in soil fungal communities (Figure 3). Adonis analysis was used to estimate whether there were significant differences in fungal community profiles among all combined remediation treatments (Table 3). PCoA showed that the soil fungal community structure of both biochar–livestock manure treatments (BG and BF) was significantly separated from that of the biochar–organic fertilizer treatment (BD) (Table 3, p < 0.05). However, the soil fungal community structures of the cover crops–biochar–organic fertilizer combined remediation treatments were not significantly separated (Table 3).

3.3. The Enriched Differential Fungi

The identification of indicator taxa is important for explaining the biological mechanisms underlying the differences in community structure among different combined remediation treatments. LEfSe was performed to identify and compare the significantly differentially enriched microorganisms in each treatment. Biomarker fungi were depicted in branching plots and subsequently subjected to linear discriminant analysis (LDA score >2) (Figure 4). The two groups of treatments with cover crops–biochar–organic fertilizer treatments and with biochar–organic fertilizer treatments were screened for 6 and 11 fungal microbial markers, respectively. It was found that the differentially enriched fungi in the Paspalum wettsteinii cover crops–biochar–organic fertilizer (PBD) treatment shifted towards f_Glomerellaceae, Archaeosporaceae, and Cystobasidiomycetes (Figure 4a and Figure A1). The differentially enriched fungi under different biochar–organic fertilizer treatments shifted towards Pleosporales and Glomeromycota (Figure 4b and Figure A2). More importantly, the results showed that the biochar–organic fertilizer (BD) treatment indicator fungi were Sordariales and Diaporthaceae (Figure 4b and Figure A2).

3.4. Relationship between Soil Physicochemical Properties and the Fungal Community

Assessing the effects of environmental factors on fungal community structure is essential to infer the underlying mechanisms governing fungal community assembly. Using fungal communities as response variables and soil physicochemical properties as explanatory variables, RDA and variance partitioning analysis (VPA) were conducted to explore the relationship between fungal community species’ composition and the soil environment to clarify the driving factors of fungal community recruitment in rare earth tailings soil grown with navel orange under different combined remediation treatments. Based on the RDA results (Figure 5) of the 11 dominant phyla (including Others) and environmental factors (Figure 5a), it was found that 77.44% and 20.24% of the variance was explained by the RDA1 and RDA2 axes, respectively, for a total explanation rate of 97.68%. Figure 5b shows that 95.26% and 0.32% of the variance was explained by RDA1 and RDA2, respectively, with the two axes together explaining 95.58%.
Different main factors affected fungal community recruitment in the different combined remediation treatments. VPA of the different cover crops–biochar–organic fertilizer treatments (Figure 6a) showed that pH (2.5%) explained the highest variation in fungal communities, followed by pH SOC (2.29%) and soil nutrients explained (−7.5%). VPA of the different biochar–organic fertilizer treatments (Figure 6b) showed that SOC (28.5%) explained the highest variation in fungal communities, followed by pH (11.6%) and soil nutrients (−36.9%). Through VPA, it was observed that pH and SOC were the major contributors to fungal community variation.

4. Discussion

Cover crops (CCs) can effectively control soil erosion [27] and have positive impacts on soil physical and biological processes [28]. Jing et al. [29] showed that cover crops are a sustainable option for improving soil microbial communities and that crop species can alter the soil microbial community. Our study also found that cover crops can alter soil fungal communities. In this study, compared to BD, Trifolium repens L. (TBD) treatment decreased the relative abundance of Glomeromycota, while Paspalum wettsteinii (PBD) treatment had the opposite effect. Root exudates are essential for plants to assemble a functional microbiome, and the inconsistent variation in the relative abundance of Glomeromycota is likely due to leguminous plants secreting more nutrients, such as amino acids, sugars, and flavonoids [30]. Our study showed a decrease in the relative abundance of Ascomycota in soils under different cover crops for two and a half years compared to the control (BD), a result consistent with the results of studies on changes in soil fungal community structure in orchards under grass cover for different numbers of years [31]. The decrease in the relative abundance of Ascomycota under cover crops for two and a half years may be due to the instability of the soil environment during the early stages of plant recovery [32]. A study has shown that Basidiomycota responds to environmental stress in contrasting ways compared to Ascomycota [33]. In the present study, our findings also demonstrated this (Figure 5). In addition, we found that the legume Trifolium repens L. (TBD) recruited more Basidiomycota fungi than the gramineous plant Paspalum wettsteinii (PBD). Zhou et al. [34] studied the structural variation in soil microbial communities of different legumes and gramineous plant species and found that the relative abundance of Basidiomycota enriched in the soil of gramineous species was higher than that of legumes. However, the soil used for their potting experiments was orchard soil that had been managed for more than 30 years, and the soil type and nutrient conditions were significantly different from our study. Fertilizers can change the quantity and quality of plant carbon input to influence soil fungal communities [35,36]. Therefore, the legume Trifolium repens L. (TBD) recruited more Basidiomycota fungi than the gramineous plant Paspalum wettsteinii (PBD), which may have been caused by the combined effects of organic fertilizer and cover crops, and this needs to be further explored.
Biochar as an amendment has attracted widespread attention. Many studies have recognized the benefits of biochar for soil improvement, as it improves soil fertility, soil structure, soil microbial communities, and soil carbon sequestration [37,38,39]. Both biochar and livestock manure are organic amendments. Livestock manure organic materials decompose slowly and can continuously release nutrients, providing a better habitat and energy for the growth of soil microorganisms. Biochar–livestock manure–organic fertilizers caused specific changes in microbial community structure when co-applied, which were dependent on the original organic material [40]. This study found a similar result. The relative abundance of Glomeromycota in the biochar–livestock manure treatments was higher than that in the biochar–organic fertilizer combined remediation treatment (BD). This may be due to the different soil AP contents after biochar–different organic fertilizer treatments (Table 1). According to the results of the RDA (Figure 5b), AP was negatively correlated with the phylum Glomeromycota. Nearly 300 kinds of arbuscular mycorrhizal (AM) fungi are crucial symbiotic fungi of plant roots. The activation of phosphorus by AM fungi is related to their dependence on effective phosphorus, and the mycorrhizal dependence of AM fungi on AP may be positive within a certain threshold, but beyond it, the dependence may be reversed [41].
Indicator microorganisms can reflect specific environmental conditions. Comparing indicator fungi from different treatment groups can provide a basis for identifying the function of fungi and evaluating the effect of different combined remediations on driving rare earth tailings soil environments. Different fungal species have different abilities to deal with various nutrient forms in soil. AM fungi can form an absolute symbiotic relationship with plants, which is the key for early plants to adapt to the terrestrial environment [42]. AM fungi are specialized symbiotic fungi that improve crop productivity by increasing the uptake of water and nutrients such as nitrogen (N), phosphorus (P), and potassium (K) [43]. Glomeromycota was observed in different combined remediation treatments, especially in the Paspalum wettsteinii (PBD) and biochar–organic fertilizer (BG) treatments. This indicated that the PBD and BG combined restoration treatments were more conducive to the restoration of the plant–soil system of rare earth tailings soil. The biochar–organic fertilizer (BD) combined restoration treatment indicator fungi were Sordariales and Diaporthaceae (Figure 4b). Ascomycota is commonly found in cultivated soils, with a complex membership of beneficial and harmful fungi. Previous research revealed that members of Sordariomycetes facilitate nutrient cycling and manure compost degradation [33]. This type genus Diaporthe in the phylum Ascomycota is widely distributed in citrus and may cause citrus disease [44]. However, no Diaporthe-caused fungal diseases were detected in the navel orange plants grown in tailings soil under combined remediation with biochar and organic fertilizer. Enhanced navel orange tree management may be needed to prevent citrus diseases. In particular, long-term monitoring of citrus growth and disease control is needed under biochar–organic fertilizer (BD) combined restoration treatment.
Ecological resilience is closely related to species richness, which is determined by the spatial and temporal heterogeneity and structural complexity of the natural habitat [45]. However, fungal community structure is not determined by a single factor but rather is related to many factors. There were some differences in soil physicochemical properties among the treatments due to the different combined remediations (Table 1). These differences could be responsible for the changes in soil fungal communities under different combined remediations. VPA confirmed this possibility. The relationship between fertilizer and soil pH is inconsistent; cattle manure had lower levels of CaCO3 relative to pig manure because of their grass diet in comparison to the CaCO3-rich diet of the pig [46]. We found a similar result: the biochar–cattle manure (BF) treatment had a significantly lower pH than the biochar–pig manure (BG) treatment. In this study, the pH of all treatments was between 7 and 8 except for the biochar–cattle manure (BF) treatment. Many studies have found that soil pH is the determinant of bacterial community variation [47,48], and fungal community structure is closely related to soil nutrient content [49]. This study showed that pH and SOC were the most important drivers of soil fungal communities in rare earth tailings–navel orange cultivation soil under different cover crops–biochar–organic fertilizer and different biochar–organic fertilizer treatments, respectively (Figure 6). The influence of soil pH on soil fungal communities may be due to the different adaptation capacities of fungal species to pH; most Ascomycota and Basidiomycota are saprophytic fungi, and the pH range for saprophytic fungi is 7–8 [50]. Moreover, SOC was the main determinant of fungal community changes, probably because of significant differences in SOC content between biochar–different organic fertilizer treatments, with lower SOC in soils under the biochar–livestock manure than under the biochar–organic fertilizer treatments. We suggest that this may be the result of the combined effect of soil microbial respiration and soil leaching after biochar–livestock manure–organic fertilizer addition.

5. Conclusions

This study was conducted to understand the response of fungal groups in rare earth tailings soil to different combined remediations, identify the biological driving factors of crop diversity–productivity relationships, and optimize the current tailings improvement and remediation measures to promote the colonization and reproduction of beneficial fungal microorganisms and improve the sustainability of remediation. To that end, the association between soil physicochemical factors and fungal species composition and diversity was analysed, which showed that soil pH and SOC had the greatest effect on the structure of fungal communities. Cover crops and livestock manure can reduce the incidence of diseases in navel oranges grown on improved tailings soils and can enhance the beneficial AM fungal taxa in the soil. In particular, the biochar–pig manure (BG) and Paspalum wettsteinii cover crops–biochar–organic fertilizer (PBD) treatments increased AM fungal colonization. Comprehensive analysis of soil environment and fungal communities, Paspalum wettsteinii cover crops–biochar–organic fertilizer, and biochar–pig manure combined remediations are the most suitable combined remediations for rare earth tailings–navel orange planting promotion. In the future, more comprehensive research is needed to develop strategies to conserve and utilize soil fungal resources to promote soil health and increase the productivity of waste rare earth tailings soils.

Author Contributions

W.L. conceptualized the study; Y.W. and F.P. identified, processed, and collected samples with help from Q.W. and J.L.; Y.W. and F.P. primarily interpreted the data with help from Q.Z., Y.P. and C.W.; Y.W. wrote the manuscript. All authors have read and agreed to the published version of the manuscript.

Funding

This study was supported by the National Natural Science Foundation of China (Grant nos. 31960302, 42007042), the Science and technology project of Jiangxi Water Resources Department (202223TGKT02), and the Forestry Science and Technology Innovation Special Project of Jiangxi Provincial Department of Forestry (Innovation Special Project, 2019 No. 25).

Data Availability Statement

Not applicable.

Conflicts of Interest

The authors declare no conflict of interest.

Abbreviations

AM fungi, arbuscular mycorrhizal fungi; AP, available phosphorus; BD, biochar–organic fertilizer; BG, biochar–pig manure; BF, biochar–cattle manure; LEfSe, linear discriminant analysis effect size; PBD, Paspalum wettsteinii cover crops–biochar–organic fertilizer; PCoA, principal coordinates analysis; RDA, redundancy analysis; SOC, soil organic carbon; TBD, Trifolium repens L. cover crops–biochar–organic fertilizer; TN, total nitrogen; TP, total phosphorus; TK, total potassium; VPA, variance partitioning analysis.

Appendix A

Forests 13 01987 g0a1 550
Figure A1. The indicator fungi with LDA scores > 2 in fungal communities were associated with different cover crops–biochar–organic fertilizer treatments.
Figure A1. The indicator fungi with LDA scores > 2 in fungal communities were associated with different cover crops–biochar–organic fertilizer treatments.
Forests 13 01987 g0a1
Forests 13 01987 g0a2 550
Figure A2. The indicator fungi with LDA scores > 2 in fungal communities were associated with different biochar–organic fertilizer treatments.
Figure A2. The indicator fungi with LDA scores > 2 in fungal communities were associated with different biochar–organic fertilizer treatments.
Forests 13 01987 g0a2
Table
Table A1. Settings for each treatment.
Table A1. Settings for each treatment.
TreatmentsBiocharOrganic FertilizerPig ManureCattle Manure
BD0.720--
TBD0.720--
PBD0.720--
BG0.7-20-
BF0.7--20
Biochar, organic fertilizer, pig manure, and cattle manure units are kg/tree. Organic fertilizer comes from organic fertilizer (N + P2O5 + K2O ≥ 5.0%, organic matter ≥ 45%) produced by Shenzhen Patan Co., LTD. (Shenzhen, China). The biochar was purchased from Jiangxi Yichun Shengyan New Energy Co., Ltd. (Yichun, China).
Table
Table A2. Main properties of soil amendments.
Table A2. Main properties of soil amendments.
AdditionspHSOM (g·kg−1)AN (mg·kg−1)AP (mg·kg−1)AK (mg·kg−1)
Biochar8.1363.123.85557.38106.04
Coal fly ash7.7984.276.65281.15158.24

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Forests 13 01987 g001 550
Figure 1. Experimental site and sampling details. (a) Location of the experimental site; (b) process of changing the soil to grow navel oranges; (c) distribution scheme of each treatment in the test area; and (d) distribution of the holes and sampling points.
Figure 1. Experimental site and sampling details. (a) Location of the experimental site; (b) process of changing the soil to grow navel oranges; (c) distribution scheme of each treatment in the test area; and (d) distribution of the holes and sampling points.
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Forests 13 01987 g002 550
Figure 2. Distributions of fungi in different treatments (phylum level). BD, biochar–organic fertilizer; TBD, Trifolium repens L. cover crops–biochar–organic fertilizer; PBD, Paspalum wettsteinii cover crops–biochar–organic fertilizer; BG, biochar–pig manure; BF, biochar–cattle manure.
Figure 2. Distributions of fungi in different treatments (phylum level). BD, biochar–organic fertilizer; TBD, Trifolium repens L. cover crops–biochar–organic fertilizer; PBD, Paspalum wettsteinii cover crops–biochar–organic fertilizer; BG, biochar–pig manure; BF, biochar–cattle manure.
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Forests 13 01987 g003 550
Figure 3. Principal coordinate analysis (PCoA) of soil fungal communities under different treatments based on the Bray–Curtis distance. BD, biochar–organic fertilizer; TBD, Trifolium repens L. cover crops–biochar–organic fertilizer; PBD, Paspalum wettsteinii cover crops–biochar–organic fertilizer; BG, biochar–pig manure; BF, biochar–cattle manure.
Figure 3. Principal coordinate analysis (PCoA) of soil fungal communities under different treatments based on the Bray–Curtis distance. BD, biochar–organic fertilizer; TBD, Trifolium repens L. cover crops–biochar–organic fertilizer; PBD, Paspalum wettsteinii cover crops–biochar–organic fertilizer; BG, biochar–pig manure; BF, biochar–cattle manure.
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Forests 13 01987 g004 550
Figure 4. Linear discriminant analysis effect size (LEfSe) of the fungal community in the different treatments. Fungal biomarkers with significantly different LDA scores > 2 among different cover crops–biochar–organic fertilizer treatments (a) and different biochar–organic fertilizer treatments (b) groups are listed. In the evolutionary branching diagram, the circles radiating from inside to outside represent taxonomic levels from phylum to genus. Different colors indicate different treatments, and species with no significant differences are uniformly colored yellow; if a group is missing in the figure, it indicates that there are no species with significant differences in this group. The names of species indicated by letters in the figure are shown in the legend below it.
Figure 4. Linear discriminant analysis effect size (LEfSe) of the fungal community in the different treatments. Fungal biomarkers with significantly different LDA scores > 2 among different cover crops–biochar–organic fertilizer treatments (a) and different biochar–organic fertilizer treatments (b) groups are listed. In the evolutionary branching diagram, the circles radiating from inside to outside represent taxonomic levels from phylum to genus. Different colors indicate different treatments, and species with no significant differences are uniformly colored yellow; if a group is missing in the figure, it indicates that there are no species with significant differences in this group. The names of species indicated by letters in the figure are shown in the legend below it.
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Figure 5. Redundancy analysis of the dominant soil fungal phyla and soil environmental factors. Different cover crops–biochar–organic fertilizer treatments (a) and different biochar–organic fertilizer treatments (b) groups are listed. Environmental factors are indicated by red arrows, and species are indicated by blue arrows. Different color circles represent each treatment.
Figure 5. Redundancy analysis of the dominant soil fungal phyla and soil environmental factors. Different cover crops–biochar–organic fertilizer treatments (a) and different biochar–organic fertilizer treatments (b) groups are listed. Environmental factors are indicated by red arrows, and species are indicated by blue arrows. Different color circles represent each treatment.
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Figure 6. Variation partitioning results in the RDA of ‘Var-part-3groups-Conditional-effects-tested’. Different cover crops–biochar–organic fertilizer treatments (a) and different biochar–organic fertilizer treatments (b) groups are listed.
Figure 6. Variation partitioning results in the RDA of ‘Var-part-3groups-Conditional-effects-tested’. Different cover crops–biochar–organic fertilizer treatments (a) and different biochar–organic fertilizer treatments (b) groups are listed.
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Table
Table 1. Soil physicochemical parameters under different treatments. (a). Soil physicochemical parameters under different cover crops–biochar–organic fertilizer treatments. (b). Soil physicochemical parameters under different biochar–organic fertilizer treatments.
Table 1. Soil physicochemical parameters under different treatments. (a). Soil physicochemical parameters under different cover crops–biochar–organic fertilizer treatments. (b). Soil physicochemical parameters under different biochar–organic fertilizer treatments.
(a)
TreatmentspHTN
(mg·g−1)		TK
(mg·g−1)		TP
(g·kg−1)		AP
(mg·kg−1)		SOC
(g·kg−1)
BD7.17 ± 0.10 a2.61 ± 0.04 a9.78 ± 0.18 a0.29 ± 0.01 a10.00 ± 2.05 a42.05 ± 2.35 a
TBD7.23 ± 0.54 a2.63 ± 0.01 a9.43 ± 0.15 a0.28 ± 0.01 a9.79 ± 1.03 a46.84 ± 4.46 a
PBD7.05 ± 0.16 a2.52 ± 0.04 a9.72 ± 0.12 a0.28 ± 0.00 a13.08 ± 0.84 a43.44 ± 3.28 a
(b)
TreatmentspHTN
(mg·g−1)		TK
(mg·g−1)		TP
(g·kg−1)		AP
(mg·kg−1)		SOC
(g·kg−1)
BD7.17 ± 0.10 a2.61 ± 0.04 ab9.78 ± 0.18 b0.29 ± 0.01 a10.00 ± 2.05 a42.05 ± 2.35 a
BG7.18 ± 0.08 a2.59 ± 0.01 b9.51 ± 0.07 b0.25 ± 0.00 a9.58 ± 1.21 a22.94 ± 1.16 b
BF6.85 ± 0.03 b2.81 ± 0.09 a10.97 ± 0.09 a0.28 ± 0.01 a11.96 ± 0.32 a23.58 ± 0.69 b
TN, total nitrogen; TK, total potassium; TP, total phosphorus; AP, available phosphorus; SOC, soil organic carbon; BD, biochar–organic fertilizer; TBD, Trifolium repens L. cover crops–biochar–organic fertilizer; PBD, Paspalum wettsteinii cover crops–biochar–organic fertilizer; BG, biochar–pig manure; BF, biochar–cattle manure. The results are presented as the mean ± standard deviation (SD). Different lowercase letters within a column indicate significant differences at the p < 0.05 level among the different treatments.
Table
Table 2. Soil fungal diversity (Shannon and Simpson indices), abundance (Chao1 estimator), and coverage under combined remediation treatments. (a). Soil fungal diversity, abundance, and coverage under different cover crops–biochar–organic fertilizer treatments. (b). Soil fungal diversity, abundance, and coverage under different biochar–organic fertilizer treatments.
Table 2. Soil fungal diversity (Shannon and Simpson indices), abundance (Chao1 estimator), and coverage under combined remediation treatments. (a). Soil fungal diversity, abundance, and coverage under different cover crops–biochar–organic fertilizer treatments. (b). Soil fungal diversity, abundance, and coverage under different biochar–organic fertilizer treatments.
(a)
TreatmentsShannon IndexSimpson IndexChao1 EstimatorCoverage
BD5.9183 ± 0.2974 b0.945 ± 0.014 b845.75 ± 25.12 a0.9983 ± 0.0005 a
TBD5.0986 ± 0.4063 a0.914 ± 0.018 a685.33 ± 96.26 a0.9983 ± 0.0005 a
PBD5.8540 ± 0.2848 a0.954 ± 0.011 a828.88 ± 99.56 a0.9983 ± 0.0005 a
(b)
TreatmentsShannon IndexSimpson IndexChao1 EstimatorCoverage
BD5.9183 ± 0.2974 a0.945 ± 0.014 a845.75 ± 25.12 a0.9983 ± 0.0005 a
BG5.5056 ± 0.2983 a0.942 ± 0.016 a796.15 ± 43.63 a0.9980 ± 0.0000 a
BF5.0896 ± 1.0256 a0.885 ± 0.102 a803.04 ± 117.30 a0.9980 ± 0.0000 a
Results are presented as the mean ± standard deviation (SD). Different lowercase letters within a column indicate significant differences at the p < 0.05 level among the different treatments. BD, biochar–organic fertilizer; TBD, Trifolium repens L. cover crops–biochar–organic fertilizer; PBD, Paspalum wettsteinii cover crops–biochar–organic fertilizer; BG, biochar–pig manure; BF, biochar–cattle manure.
Table
Table 3. Adonis analysis of soil community structure between combined remediation treatments.
Table 3. Adonis analysis of soil community structure between combined remediation treatments.
Vs_TreatmentDfSums of SquaresFR2p
TBD-BD10.171270.968030.194850.5
BD-PBD10.170241.43950.264640.1014
TBD-PBD10.267331.43470.263990.2
BG-BD10.362233.1470.440320.001389
BF-BG10.18931.3720.255390.1014
BF-BD10.432513.28330.45080.001389
Df, degree of freedom; Sums of Squares, sum of deviation squares. BD, biochar–organic fertilizer; TBD, Trifolium repens L. cover crops–biochar–organic fertilizer; PBD, Paspalum wettsteinii cover crops–biochar–organic fertilizer; BG, biochar–pig manure; BF, biochar–cattle manure.
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Wang, Y.; Pan, F.; Wang, Q.; Luo, J.; Zhang, Q.; Pan, Y.; Wu, C.; Liu, W. The Effect of Different Remediation Treatments on Soil Fungal Communities in Rare Earth Tailings Soil. Forests 2022, 13, 1987. https://doi.org/10.3390/f13121987

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Wang Y, Pan F, Wang Q, Luo J, Zhang Q, Pan Y, Wu C, Liu W. The Effect of Different Remediation Treatments on Soil Fungal Communities in Rare Earth Tailings Soil. Forests. 2022; 13(12):1987. https://doi.org/10.3390/f13121987

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Wang, Yu, Feng Pan, Qiong Wang, Jie Luo, Qin Zhang, Yingying Pan, Chenliang Wu, and Wei Liu. 2022. "The Effect of Different Remediation Treatments on Soil Fungal Communities in Rare Earth Tailings Soil" Forests 13, no. 12: 1987. https://doi.org/10.3390/f13121987

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